similar to: Vignette using parallel's makeCluster function has trouble building on Windows 7

Hi, again- But I see the behavior has been fixed in the current R-devel build, so sorry for the noise, and thanks for keeping R such a great package! --Rich Calaway _____________________________________________ From: Rich Calaway [mailto:richcalaway at revolution-computing.com] Sent: Wednesday, September 23, 2009 12:32 PM To: 'R-bugs at R-project.org' Subject: RE: Bug 13937

Hi, this post is about foreach operators, the compiler package and the last update of doMC that includes support for the compiler functionality. I am using a home-made %dopar%-like operator that adds some custom expression to be executed before the foreach loop expression itself (see sample code below). It used to work perfectly with doMC 1.2.1, but with the introduction of the compiler

Hi, I'm trying to submit my first package which depends on doParallel: Depends: R (>= 3.0), igraph, doParallel Running hadley devtools: devtools::check() and devtools::release() result in no problem (no ERROR nor NOTE on Linux, Mac and Windows). However, when in use the devtools::build_win() command, it results in the following note: * checking R code for possible problems ... NOTE

On 05/03/2015 6:16 PM, Brian G. Peterson wrote: > On Thu, 2015-03-05 at 18:03 -0500, Etienne Lord wrote: >> Hi, >> >> I'm trying to submit my first package which depends on doParallel: >> >> Depends: R (>= 3.0), igraph, doParallel > > add foreach to your Depends. That should resolve the error you're > seeing. Please don't do that. Use

Trying to install RMySQL on 64-bit Windows 7. Using R-2.14.2 with Rtools214 and MySQL Server 5.5. Read through several step-by-steps of RMySQL source installation. Troubleshooting: - Copied libmysql.dll to R-2.14.2/bin AND R-2.14.2/bin/i386. - Copied libmysql.dll and libmysql.lib to MySQL Server 5.5\lib\opt. - Entered MYSQL_HOME=C:\Program Files\MySQL\MySQL Server 5.5 into Renviron.site,

Hello: Could you please suggest the best way to become an "advanced" R programmer. I went through "R for dummies" by de Vries and Meys and I can see two ways to proceed: 1) Get a more advanced textbook. E.g. could you recommend Gentleman, "R for Bioinformatics"? 2) Because textbooks are limited and become obsolete fast, I can focus on learning state-of-the-art

Buenas, Quiero ver si he paralelizado correctamente el proceso. Tengo dos dataframes, A y B y quiero calcular la distancia euclídea de todas las filas de A sobre todas las filas de B. Para ello he hecho lo siguiente #cargo las librerias library(foreach) library(doParallel) #establezco el numero de clusters, en mi caso 4, ya que el procesador tiene 4 nucleos cl<-makeCluster(4)

I'm working on an update for my CRAN package "spatial.tools" and I noticed a new warning when running R CMD CHECK --as-cran: * checking CRAN incoming feasibility ... NOTE Maintainer: 'Jonathan Asher Greenberg <spatial-tools@estarcion.net>' Depends: includes the non-default packages: 'sp' 'raster' 'rgdal' 'mmap' 'abind'

Hello all: Please help me with this "can't find object" issue. I'm trying to get leave-one-out predicted values for Beta-binomial regression. It may be the gamlss issue because the code seems to work when %do% is used. I have searched for similar issues, but haven't managed to figure it out. This is on Windows 10 platform. Thanks in advance, Nik #

See Hadley's advanced R along Thomas Mailund's books. I haven't gone through them carefully but they both seem (from what I've looked at ) to be the best ones for that. Mentions of others are appreciated. On Tue, Mar 13, 2018 at 5:26 PM, Nik Tuzov <ntuzov at beacon.partek.com> wrote: > > Hello: > > Could you please suggest the best way to become an

Hello, I have been having issues using parallel::mclapply in a memory-efficient way and would like some guidance. I am using a 40 core machine with 96 GB of RAM. I've tried to run mclapply with 20, 30, and 40 mc.cores and it has practically brought the machine to a standstill each time to the point where I do a hard reset. When running mclapply with 10 mc.cores, I can see that each process

Thanks for the quick reply. Adding all the dependencies of doParallel (foreach, parallel, iterators) in the DESCRIPTION and in import statements in NAMESPACE resolved the build_win problems. Don't know why this is required for Windows build. Thanks again. 2015-03-05 18:22 GMT-05:00 Duncan Murdoch <murdoch.duncan at gmail.com>: > On 05/03/2015 6:16 PM, Brian G. Peterson wrote: >

I'd be curious to know what others think of Rich's patch. If it is acceptable, I can spend time that I was going to look at it this week on another bug. -----Original Message----- From: Rich Calaway Sent: Friday, June 23, 2017 6:34 PM To: Nathan Sosnovske <nsosnov at microsoft.com>; Duncan Murdoch <murdoch.duncan at gmail.com>; Andrie de Vries <apdevries at gmail.com>

If the code you are running in parallel is complicated, maybe foreach is not sophisticated enough to find all the variables you refer to. Maybe use parallel::clusterExport yourself? But be a aware that passing parameters is much safer than directly accessing globals in parallel processing, so this might just be your warning to not do that anyway. -- Sent from my phone. Please excuse my brevity.

I checked after this question popped up on Stackoverflow: https://stackoverflow.com/questions/44785961/compile-pdf-in-rstudio-works-but-knit2pdf-does-not-work-in-r-or-rstudio On Windows, texi2pdf looks for the texify.exe of Miktex, but looks in a very wrong place: > Sys.which("texify") texify

Oh, I completely missed that one. It's very neat as it seems to work both on Windows and Unix. Thanks! Xavier On 10/02/15 10:52, Martyn Plummer wrote: > The CRAN package snow is superseded by the parallel package which is > distributed with R since version 2.14.0. Here are the release notes > > \item There is a new package \pkg{parallel}. > > It incorporates (slightly

Dear R helpers, I have what another member on this forum described as an embarrassingly parallel problem. I am trying to fit models on subsets of some data based on unique combinations of two id factors in the dataset. Total number of combinations is 30^5, and this takes a long time. So, I would like fit models for each of the datasets produced by subsetting on the unique combinations, splitting

Dear R-SIG-Debian, I am using R version 3.1.2 with rstudio-server 0.98.113 on debian build 3.2.0-4-amd64 #1 SMP Debian 3.2.68-1+deb7u1 x86_64 GNU/Linux. I often use the %dopar% operator in from the foreach package to run code in parallel. However, the only other use on the box seemingly installed a few items and suddenly %dopar% will use far more than the number of cores I am specifying and

I am trying to run the following code in R on a Linux cluster. I would like to use the full processing power (specifying cores/nodes/memory). The code essentially runs predictions based on a GAM regression and saves the results as a CSV file for multiple sets of data (here I only show two). Is it possible to run this code using HPC packages such as Rmpi/snow/doParallel? Thank you!

>>>>> Nathan Sosnovske via R-devel <r-devel at r-project.org> >>>>> on Mon, 26 Jun 2017 18:22:25 +0000 writes: > I'd be curious to know what others think of Rich's > patch. If it is acceptable, I can spend time that I was > going to look at it this week on another bug. It is a bit kludgy (*) of course, but I confirm it solves